While many important RNA sequences have been determined, there is little definitive secondary and three-dimensional (3D) structure information about RNA. Several algorithms have been developed to predict RNA secondary structure from sequence; however, the lack of experimental parameters for non-Watson-Crick regions is a major limitation of these algorithms. NMR and X-ray crystallography are powerful tools to determine RNA 3D structure; however, these techniques are time and labor intensive. Thus, there is a need for reliable, rapid methods to predict secondary and 3D structures of RNA from sequence. Therefore, the broad, long-term objective of the PI's laboratory is to improve RNA secondary and tertiary structure prediction from sequence. In order to achieve this long-term objective, it is essential to understand RNA thermodynamics and structure and how these properties are related. Improved nearest neighbor parameters derived from thermodynamic data can improve secondary structure prediction from sequence. In order to improve tertiary structure prediction, knowledge about the structural features of secondary structure motifs in previously solved three-dimensional structures and NMR data for previously unstudied motifs would be beneficial. Computational techniques can be used to understand the relationship between RNA thermodynamics and RNA structure. Therefore, this proposal begins to investigate the thermodynamics, structures, and energetics of common RNA secondary structure motifs. The specific objectives of the proposed research are: (1) to address the major limitations of the current algorithms used to predict secondary structure from sequence, (2) to identify structural patterns of secondary structure motifs in 3D structures, and (3) to investigate the relationship between RNA stability and structure on a molecular level via computational techniques. The research design and methods for achieving these goals include: optical melting experiments, an in-depth analysis of previously solved RNA structures, the use of NMR to identify structural properties of underrepresented RNA motifs, and hydrogen bonding and base stacking calculations. This proposed research is relevant to the mission of the NIH and the objectives of the AREA Grant program. An improved method to predict RNA secondary and tertiary structure from sequence is essential to move the field of RNA research forward and should impact researchers in any field relying on RNA structure prediction, especially those attempting to understand the structure-function relationship of RNA, understand the interactions of RNA with other biological molecules, and target RNA with therapeutics. As a result, the proposed research will advance the Nation's capacity to protect and improve health, expand the knowledge base in medical and associated sciences, and benefit available students through exposure to and participation in research in the biomedical sciences.